#20 Data Loading in RAG Pipeline | Build RAG Application using LangChain #rag #langchain

Description

In this video, we explore the crucial first step of building a RAG pipeline - loading data from different sources using LangChain's Document Loaders. 🔧 Document Loaders Covered: TextLoader - Load data from .txt files PyPDFLoader - Extract content from PDF documents (multi-page support) CSVLoader - Load structured data from CSV files (30,000+ records example) WebBaseLoader - Scrape and load web page content WikipediaLoader - Fetch data directly from Wikipedia 💻 Technologies: Python | LangChain | PyPDF | BeautifulSoup4 | Wikipedia API 🎯 Perfect For: Developers learning GenAI, full-stack AI development, LangChain agents, and building production-ready chatbots from basic to advanced level. IMPORTANT RESOURCES: 📂 GitHub Repository: https://github.com/techsimpluslearning/Complete-GenAI-Course-Python-Langchain 💬 Discord Community: https://discord.gg/Y5gASsas9j Telegram Group: https://t.me/+ZILeEp0hvjVmNmE9 If you have any questions or doubts, feel free to reach out to me. 📞 Schedule 1-to-1 Call: https://topmate.io/techsimplus_learnings Enjoying the content? LIKE 👍 this Video, SUBSCRIBE 🔔 for Data Science, Machine Learning, Deep Learning and Generative AI tutorials, and COMMENT below if you have any questions, doubts or Suggestions! 🚀 Let's master GenAI together! 🚀🔥 #generativeai #langchain #python #ai #machinelearning #aiprojects #langgraph #rag #aiagents #openai #gemini #awsbedrock #fastapi #modelcontextprotocol #streamlit #aitutorial #learnai #coding #programming #indianyoutuber #hinditutorial #techeducation #aicourses #portfolio #careergrowth #vectordatabases #aideployment #2026 #deeplearning #nlp #chatgpt #gemini #genai #techsimplus #ollama #groq #grok #aiagents #ai #gpt #rag #vectordatabases #embeddings